Instructions to use webis/monoelectra-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Lightning IR
How to use webis/monoelectra-large with Lightning IR:
#install from https://github.com/webis-de/lightning-ir from lightning_ir import CrossEncoderModule model = CrossEncoderModule("webis/monoelectra-large") model.score("query", ["doc1", "doc2", "doc3"]) - Notebooks
- Google Colab
- Kaggle
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- cross-encoder
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This repository contains the model described in the paper [
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The code for training and evaluation can be found at https://github.com/webis-de/msmarco-llm-distillation.
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- cross-encoder
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This repository contains the model described in the paper [Rank-DistiLLM: Closing the Effectiveness Gap Between Cross-Encoders and LLMs for Passage Re-Ranking](https://arxiv.org/abs/2405.07920).
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The code for training and evaluation can be found at https://github.com/webis-de/msmarco-llm-distillation.
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